Forward Deployed Engineer, Lead - LLM Post-training

Reflectionai is focused on building open superintelligence and making it accessible to all. They are seeking a technical leader to build and scale their post-training and evaluation capabilities within the Applied AI team, owning the strategy for model customization and working directly with customers.

Responsibilities:

• Lead post-training engagements with enterprise customers: assess their data, define training strategies, design reward signals and verifiers, prepare datasets, run training loops, and evaluate results against customer-specific benchmarks
• Design and build RL training environments for model adaptation, including synthetic data generation pipelines, reward model training, and preference data collection workflows
• Design and build evaluation infrastructure: define what 'better' means for each customer use case, build eval harnesses, curate test sets, and establish baselines that measure real-world performance
• Own the data pipeline from raw customer data through training-ready datasets, including synthetic data generation, data quality inspection, cleaning, and format standardization
• Deploy post-trained models across hybrid environments (public cloud, VPC, and on-premises), working with infrastructure teams to ensure inference performance, cost efficiency, and reliability at scale
• Shape and scale the post-training and evaluation practice by defining playbooks, best practices, and technical standards. Mentor engineers on the team and help define what great applied AI work looks like at Reflection